Development and characterization of liposomal formulation containing phytosterols and tocopherols for reducing low-density lipoprotein cholesterol.
Bibliographic record
Abstract
Purpose: Phytosterols are plant sterols with structural resemblance to cholesterol. United States Food and Drug Administration (FDA) and Health Canada have approved phytosterols as a cholesterol-lowering agent due to their ability to significantly reduce low-density lipoprotein cholesterol (LDL-C) in the range of 7-12%. However, phytosterols (lipophilic) have the potential to impart higher efficacy in the reduction of LDL-C if formulated in a delivery system that increases its bioavailability. In this work, we aim to develop and characterize a liposomal formulation containing phytosterols and tocopherols; the aim is to enhance cholesterol-lowering ability of phytosterols. We also aim to test the efficacy of brassicasterol (phytosterol unique to canola seeds) which has not yet been approved by the FDA. To prevent oxidation of phytosterols during formulation development and storage, tocopherols (vitamin E) are also added as antioxidants. Methods: Liposomes containing phytosterols and tocopherols were prepared using phosphatidylcholine as the lipid carrier and formulated using three different approaches -i) thin layer hydration homogenization, ii) thin layer hydration ultra-sonication, and iii) Mozafari method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated for quantifying liposomal phytosterols and tocopherols. Results: Liposomal vesicles prepared via homogenization and ultrasonication methods were significantly lower in size (<200 nm) in comparison to those produced by the Mozafari method (>200 nm). All three methods showed comparable zeta potential values (-9 to -14 mV), which is adequate for the physical stability of the vesicles. A new validated LC-MS/MS method with a total run time of seven minutes was applied to quantify four phytosterols (brassicasterol, campesterol, stigmasterol, and β-sitosterol) and three tocopherols (alpha, gamma, and delta) simultaneously. The run time of seven minutes is the shortest among reported methods to date. The liposomal formulation prepared by all three methods showed entrapment efficiency >89% for both phytosterols and tocopherols. Conclusion: Liposomes containing phytosterols and tocopherols were successfully developed and characterized with the aim of enhancing the efficacy of phytosterols. In vivo studies will be conducted using hamster animal model to compare the efficacy of liposomal phytosterols to marketed phytosterols containing products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".